scholarly journals 60. New Prognostic Markers for COVID-19 Disease

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S161-S162
Author(s):  
Amr Ramahi ◽  
Kok Hoe Chan ◽  
Laxminarayan Prabhakar ◽  
Iyad Farouji ◽  
Divya Thimmareddygari ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Prognostic Markers ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Hospitalized Patients ◽  
Prognostic Indicators ◽  
Blood Profile ◽  
New Model ◽  
D Dimer

Abstract Background A few COVID-19 related retrospective studies have established that older age, elevated neutrophil-lymphocyte ratio (NLR), and decreased lymphocyte-CRP ratio (LCR) were associated with worse outcome. Herein, we aim to identify new prognostic markers associated with mortality. Methods We conducted a retrospective hospital cohort study on patients ≥ 18 years old with confirmed COVID-19, who were admitted to our hospital between 03/15/2020 and 05/25/2020. Study individuals were recruited if they had a complete CBC profile and inflammatory markers such as CRP, ferritin, D-dimer and LDH, as well as a well-defined clinical outcomes (discharged alive or expired). Demographic, clinical and laboratory data were reviewed and retrieved. Univariate and multivariate logistic regression methods were employed to identify prognostic markers associated with mortality. Results Out of the 344 confirmed COVID-19 hospitalized patients during the study period, 31 who did not have a complete blood profile were excluded; 303 patients were included in the study, 89 (29%) expired, and 214 (71%) were discharged alive. Demographic analysis was tabulated in Table 1. The univariate analysis showed a significant association of death with absolute neutrophil count (ANC, p=0.022), NLR (p=002), neutrophil-monocyte ratio (NMR, p=< 0.0001), LCR (p=0.007), lymphocyte-LDH ratio (LLR, p=< 0.0001), lymphocyte-D-dimer ratio (LDR, p=< 0.0001), lymphocyte-ferritin ratio (LFR, p=< 0.0001), and platelets (p=0.037) with mortality. With multivariable logistic regression analysis, the only values that had an odds of survival were high LDR (odds ratio [OR] 1.763; 95% confidence interval [CI], 1.20–2.69), and a high LFR (OR 1.136, CI 1.01–1.34). We further build up a model which can predict >85% mortality in our cohorts with the utilization of D-dimer (>500 ng/ml), Ferritin (>200 ng/ml), LDR (< 1.6), LFR (< 4) and ANC (>2.5). This new model has a ROC of 0.68 (p< 0.0001). Conclusion This retrospective cohort study of hospitalized patients with COVID-19 suggests LDR and LFR as potential independent prognostic indicators. A new model with combination of D-dimer, Ferritin, LDR, LFR and ANC, was able to predict >85% mortality in our cohort with ROC of 0.68, it will need to be validated in a prospective cohort study. Disclosures Jihad Slim, MD, Abbvie (Speaker’s Bureau)Gilead (Speaker’s Bureau)Jansen (Speaker’s Bureau)Merck (Speaker’s Bureau)ViiV (Speaker’s Bureau)

scholarly journals 387. Markers for Mortality in COVID-19 Patients with Atrial Fibrillation or Flutter

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S262-S262
Author(s):  
Kok Hoe Chan ◽  
Bhavik Patel ◽  
Iyad Farouji ◽  
Addi Suleiman ◽  
Jihad Slim
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Prognostic Markers ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Significant Difference ◽  
New Onset

Abstract Background Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection can lead to many different cardiovascular complications, we were interested in studying prognostic markers in patients with atrial fibrillation/flutter (A. Fib/Flutter). Methods A retrospective cohort study of patients with confirmed COVID-19 and either with existing or new onset A. Fib/Flutter who were admitted to our hospital between March 15 and May 20, 2020. Demographic, outcome and laboratory data were extracted from the electronic medical record and compared between survivors and non-survivors. Univariate and multivariate logistic regression were employed to identify the prognostic markers associated with mortality in patients with A. Fib/Flutter Results The total number of confirmed COVID-19 patients during the study period was 350; 37 of them had existing or new onset A. Fib/Flutter. Twenty one (57%) expired, and 16 (43%) were discharged alive. The median age was 72 years old, ranged from 19 to 100 years old. Comorbidities were present in 33 (89%) patients, with hypertension (82%) being the most common, followed by diabetes (46%) and coronary artery disease (30%). New onset of atrial fibrillation was identified in 23 patients (70%), of whom 13 (57%) expired; 29 patients (78%) presented with atrial fibrillation with rapid ventricular response, and 2 patients (5%) with atrial flutter. Mechanical ventilation was required for 8 patients, of whom 6 expired. In univariate analysis, we found a significant difference in baseline ferritin (p=0.04), LDH (p=0.02), neutrophil-lymphocyte ratio (NLR) (p=0.05), neutrophil-monocyte ratio (NMR) (p=0.03) and platelet (p=0.015) between survivors and non-survivors. With multivariable logistic regression analysis, the only value that had an odds of survival was a low NLR (odds ratio 0.74; 95% confidence interval 0.53–0.93). Conclusion This retrospective cohort study of hospitalized patients with COVID-19 demonstrated an association of increase NLR as risk factors for death in COVID-19 patients with A. Fib/Flutter. A high NLR has been associated with increased incidence, severity and risk for stroke in atrial fibrillation patients but to our knowledge, we are first to demonstrate the utilization in mortality predictions in COVID-19 patients with A. Fib/Flutter. Disclosures Jihad Slim, MD, Abbvie (Speaker’s Bureau)Gilead (Speaker’s Bureau)Jansen (Speaker’s Bureau)Merck (Speaker’s Bureau)ViiV (Speaker’s Bureau)

Abstract 14559: Prognostic Utility of Cardiac Markers in Covid-19 Patients

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Ahmad Damati ◽  
Kok Hoe Delcos Chan ◽  
Iyad Farouji ◽  
Amr Al-ramahi ◽  
Patel Bhavic ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Univariate Analysis ◽  
Cardiovascular Complications ◽  
Hospitalized Patients ◽  
Multivariable Logistic Regression Analysis ◽  
Cardiac Markers ◽  
Significant Difference ◽  
The Us ◽  
Prognostic Utility ◽  
Artery Disease

Introduction: SARS-CoV-2 infection has been associated with a multiple cardiovascular complications. It is not known if cardiac markers can be used for outcome prediction in the US population. Methods: We conducted a retrospective study on patients ≥ 18 years old with confirmed COVID 19, who were admitted to our hospital between 03/15/2020 and 05/25/2020. Individuals were included if they had a baseline troponin and brain natriuretic peptide (BNP) available, and if their outcome by the end of the study period was well defined as discharge alive, or deceased. Univariate and multivariate logistic regression methods were employed to identify the cardiac markers associated with mortality in COVID-19 patients. Results: The total number of confirmed COVID-19 hospitalized patients during the study period was 348, after excluding patients who did not have cardiac markers available, 233 patients were included in the study, 75 (32%) expired, and 158 (68%) were discharged alive. The median age was 65 years old, and ranged from 22 to 101 years old. 140 males and 93 females. Comorbidities were present in 201 (86%) patients, with hypertension (65%) being the most common, followed by obesity (55%), diabetes mellitus (DM) (44%) and coronary artery disease (27%). Mechanical ventilation was required for 61 patients of whom 42 expired. In univariate analysis, we found a significant difference in history of chronic kidney disease defined by eGFR <45ml/min (p=0.046), DM (p=0.043), initial SOFA (p=0.017), troponin (p=0.001), BNP (p=0.043), CRP (p=<0.0001), LDH (p=<0.0001) and ferritin (p=<0.0001) between survivors and non-survivors. With multivariable logistic regression analysis, the only values that had an odds of survival were a low troponin (odds ratio [OR] 0.17; 95% confidence interval [CI], 0.04-0.52), a low SOFA (OR 0.72, CI 0.50-0.94) and a low CRP (OR 0.87, CI 0.87-0.94). Conclusions: This retrospective cohort study of hospitalized patients with COVID-19 suggests an independent association of increased troponin as risk factor for death in COVID-19 patients. Cardiac troponin has been reported as potential prognostic marker in the China cohort. To our knowledge, we are first to demonstrate the utilization of troponin as mortality predictor in the US population.

scholarly journals Prevalence of chronic chikungunya and associated risks factors in the French West Indies (La Martinique). A prospective cohort study

2019 ◽  
Author(s):  
Bertolotti Antoine ◽  
Thioune Marême ◽  
Abel Sylvie ◽  
Belrose Gilda ◽  
Calmont Isabelle ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Acute Phase ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Regression Models ◽  
Functional Disability ◽  
Univariate Analysis ◽  
Logistic Regression Models ◽  
Adequate Hydration

AbstractBackgroundThe chikungunya virus (CHIKV) is a re-emerging alphavirus that can cause chronic rheumatic musculoskeletal disorders, named chronic chikungunya (CHIKC+), which may be long-term incapacitating. A chikungunya outbreak occurred in 2013 in La Martinique. We constituted the first prospective cohort study of CHIKV-infected subjects in the Caribbean to assess the prevalence of CHIKC+ at 12 months and to search for factors present at the acute stage significantly associated with chronicity.Methodology/Principal findingsA total of 193 patients who tested positive for RT-PCR CHIKV, were submitted to clinical investigations in the acute phase (<21 days), and 3, 6, and 12 months after their inclusion. A total of 167 participants could be classified as either suffering or not from CHIKC+. They were analyzed using logistic regression models. At 12 months, the overall prevalence of CHIKC+ was 52.1% (95%CI: 44.5-59.7). In univariate analysis, age (OR: 1.04; 95% CI: 1.02-1.07; p=0.0003), being male (OR: 0.51; 95%CI: 0.27-0.98; p=0.04), headache (OR: 1.90; 95%CI: 1.02-3.56; p=0.04), vertigo (OR: 2.06; 95%CI: 1.05-4.03; p=0.04), vomiting (OR: 2.51; 95%CI: 1.07-5.87; p = 0.03), urea (OR: 1.33; 95%CI: 1.05-1.70; p=0.02) were associated with CHIKC+. In final multivariate logistic regression models for 167 participants, predictors of CHIKC+ were age (OR 1.06; 95%CI: 1.03-1.08; p<0.0001), male sex (OR: 0.40; 95%CI: 0.19-0.84; p=0.015), vertigo (OR: 2.46; 95%CI: 1.16-5.20; p=0.019), hypotension (OR 4.72; 95% -CI: 1.19-18.79; p=0.028), recoloration time >3 seconds (OR: 3.79; 95%-CI: 1.01-14.25).ConclusionsThis cohort study in La Martinique confirms that CHIKC+ is a frequent complication of acute chikungunya disease. Analysis emphasized the importance of age and female sex for CHIKC occurrence, and pointed out the potential aggravating role of dehydration at the acute phase. Early and adequate hydration could reduce the risk chronic chikungunya disorders.Author SummaryChikungunya is a mosquito-borne virus found in tropical countries that has been re-emerging in the last decade. It has caused major epidemics in recent years, such as in Reunion Island and in Southeast Asia. Nearly 2.5 billion people around the world are at risk of contracting the virus. During the acute phase of the illness, patients experience a flu-like syndrome with fever, headache, myalgia, rash, and severe arthralgia. These symptoms can persist for several months in some patients, and can lead to significant functional disability. During the 2013 epidemic in Martinique, we followed nearly 200 patients who had contracted chikungunya. More than half of the patients had a chronic form of the disease—mainly women over 50 years of age. Our statistical analyses indicate that poor hydration during the acute phase may be a risk factor for developing chronic rheumatism. Therefore, in the context of a chikungunya epidemic, it seems important to encourage patients to drink plenty of fluids as soon as the first symptoms appear.

scholarly journals Gamma-glutamyl-transferase may predict COVID-19 outcomes in hospitalized patients

2021 ◽  
Author(s):  
Ahmet Yozgat ◽  
benan kasapoglu ◽  
Alpaslan Tanoğlu ◽  
Güray Can ◽  
Yusuf Serdar Sakin ◽  
...  
Keyword(s):  
Intensive Care ◽  
Laboratory Data ◽  
Elevated Serum ◽  
Hospitalized Patients ◽  
Gamma Glutamyl Transferase ◽  
Laboratory Findings ◽  
Gamma Glutamyl ◽  
Predictive Role ◽  
Glutamyl Transferase ◽  
D Dimer

Aim: In this study, we aimed to define the predictive role of liver function tests at admission to the hospital in outcomes of hospitalized patients with COVID-19. Material and Method: In this multicentric retrospective study, a total of 269 adult patients (≥18 years of age) with confirmed COVID-19 who were hospitalized for the treatment were enrolled. Demographic features, complete medical history, and laboratory findings of the study participants at admission were obtained from the medical records. Patients were grouped regarding their ICU requirements during their hospitalization periods. Results: Among all 269 participants, 106 were hospitalized in the intensive care unit (ICU) and 66 died. The patients hospitalized in ICU were older than patients hospitalized in wards (p=0.001) and expired patients were older than alive patients (p=0.001). Age, elevated serum D-dimer, creatinine, and gamma-glutamyl transferase (GGT) levels at admission were independent factors predicting ICU hospitalization and mortality in COVID-19 patients. Conclusion: In conclusion, in hospitalized patients with COVID-19, laboratory data on admission, including serum, creatinine, GGT and d-dimer levels have an important predictive role for the ICU requirement and mortality. Since these tests are readily available in all hospitals and inexpensive, some predictive formulas may be calculated with these parameters at admission, to define the patients requiring intensive care.

scholarly journals CT characteristics and laboratory findings of COVID-19 pneumonia in relation to patient outcome

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Ibrahim A. I. Mohamed ◽  
Hosam A. Hasan ◽  
Mohamed Abdel-Tawab
Keyword(s):  
Patient Outcome ◽  
Severity Score ◽  
Patient Survival ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Laboratory Findings ◽  
Pulmonary Manifestations ◽  
The Relationship ◽  
Ct Finding ◽  
D Dimer

Abstract Background This study aimed to investigate the chest computed tomography (CT) characteristics and laboratory findings in patients with confirmed COVID-19 pneumonia and to evaluate their relationship with clinical outcome. This retrospective study assessed 164 consecutive CT chests of COVID-19 patients during April 2020. The chest CT and laboratory data were analyzed. The primary endpoint was patient survival either died or survived. The relationship between CT and laboratory findings was correlated to patient outcome. Results The study group included 164 patients (86 male, 78 women; average age, 44.3 ± 16.5 years) whose RT-PCR were positive for COVID-19. Only 120 (73.2%) patients had pulmonary manifestations. Ground glass opacities of peripheral distribution and multifocal affection were the major CT finding in COVID-19 patients. Univariate analysis revealed that CT severity score, D-dimer level, age, total leucocytic count, and absolute lymphocytic count were predictive for death. Conclusion CT has an emerging role in the diagnosis of COVID-19 pneumonia and in assessing disease severity. CT severity score, D-dimer, total leucocytic count, and absolute lymphocytic count significantly predict patient survival.

scholarly journals Predictors of hospital mortality among patients with COVID-19 in Tehran, Iran

2021 ◽  
Vol 9 ◽  
pp. 205031212110515
Author(s):  
Fatemeh Esfahanian ◽  
SeyedAhmad SeyedAlinaghi ◽  
Nazanin Janfaza ◽  
Marcarious M. Tantuoyir
Keyword(s):  
Logistic Regression ◽  
Confidence Interval ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Laboratory Data ◽  
Hospitalized Patients ◽  
Multivariate Logistic Regression ◽  
Predictors Of Mortality ◽  
Laboratory Test Results ◽  
History Of

Objective: The coronavirus disease 2019 (COVID-19) has become a global pandemic. Timely and effective predictors of survival and death rates are crucial for improving the management of COVID-19 patients. In this study, we evaluated the predictors of mortality based on the demographics, comorbidities, clinical characteristics, laboratory findings, and vital signs of 500 patients with COVID-19 admitted at Imam Khomeini Hospital Complex, the biggest hospital in Tehran, Iran. Methods: Five hundred hospitalized laboratory-confirmed COVID-19 patients were included in this study. Subsequently, electronic medical records, including patient demographics, clinical manifestation, comorbidities, and laboratory test results were collected and analyzed. They were divided into two groups: expired and discharged. Demographics, clinical, and laboratory data were compared among the two groups. The related factors with death in the patients were determined using univariate and multivariate logistic regression approaches. Results: Among the 500 hospitalized patients, most patients were male (66.4% versus 33.6%). The expired group had more patients ⩾70 years of age compared with the discharged group (32.9% versus 16.3%, respectively). Almost 66% of the expired patients were hospitalized for ⩾5 days which was higher than the discharge group (26.9%). Patients with a history of opium use in the expired group were significantly higher compared to the discharged group (14.8% versus 8.6%, p = 0.04) as well as a history of cancer (15.5% versus 4.7%, p < 0.001). Out of the 500 patients with COVID-19, four patients (2.6%) were HIV positive, all of whom expired. Dyspnea (76.4%), fever (56.6%), myalgia (59.9%), and dry cough (67%) were the most common chief complaints of hospitalized patients. Age ⩾70 years (adjusted odds ratio = 2.49; 95% confidence interval, 1.02–6.04), being female (adjusted odds ratio = 2.06; 95% confidence interval, 1.25–3.41), days of hospitalization (adjusted odds ratio = 5.73; 95% confidence interval, 3.49–9.41), and having cancer (adjusted odds ratio = 3.23; 95% confidence interval, 1.42–7.39) were identified as independent predictors of mortality among COVID-19 patients. Conclusion: Discharged and expired COVID-19 patients had distinct clinical and laboratory characteristics, which were separated by principal component analysis. The mortality risk factors for severe patients identified in this study using a multivariate logistic regression model included elderly age (⩾70 years), being female, days of hospitalization, and having cancer.

scholarly journals Predictors of Mortality in Hemodialyzed Patients after SARS-CoV-2 Infection

2022 ◽  
Vol 11 (2) ◽  
pp. 285
Author(s):  
Leszek Tylicki ◽  
Ewelina Puchalska-Reglińska ◽  
Piotr Tylicki ◽  
Aleksander Och ◽  
Karolina Polewska ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Laboratory Data ◽  
Case Fatality ◽  
Maintenance Hemodialysis ◽  
Blood Oxygen Saturation ◽  
Dialysis Unit ◽  
Regression Methods ◽  
Multivariable Logistic Regression ◽  
All Cause Mortality ◽  
D Dimer

Introduction: The determinants of COVID-19 mortality are well-characterized in the general population. Less numerous and inconsistent data are among the maintenance hemodialysis (HD) patients, who are the population most at risk of an unfavorable prognosis. Methods: In this retrospective cohort study we included all adult HD patients from the Pomeranian Voivodeship, Poland, with laboratory-confirmed SARS-CoV-2 infection hospitalized between 6 October 2020 and 28 February 2021, both those who survived, and also those who died. Demographic, clinical, treatment, and laboratory data on admission, were extracted from the electronic medical records of the dedicated hospital and patients’ dialysis unit, and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with 3-month all-cause mortality. Results: The 133 patients (53.38% males) aged 73.0 (67–79) years, with a median duration of hemodialysis of 42.0 (17–86) months, were included in this study. At diagnosis, the majority were considered to have a mild course (34 of 133 patients were asymptomatic, another 63 subjects presented mild symptoms), while 36 (27.07%) patients had low blood oxygen saturation and required oxygen supplementation. Three-month mortality was 39.08% including an in-hospital case fatality rate of 33.08%. Multivariable logistic regression showed that the frailty clinical index of 4 or greater (OR 8.36, 95%CI 1.81–38.6; p < 0.01), D-Dimer of 1500 ng/mL or greater (6.00, 1.94–18.53; p < 0.01), and CRP of >118 mg/L at admission (3.77 1.09–13.01; p = 0.04) were found to be predictive of mortality. Conclusion: Very high 3-month all-cause mortality in hospitalized HD patients was determined mainly by frailty. High CRP and D-dimer levels upon admission further confer mortality risk.

scholarly journals Covid-19 in Hospitalized Patients Admitted from Skilled Nursing Facilities: Factors Associated with Mortality

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 941-941
Author(s):  
Rongfang Zhan ◽  
Cheng Yin ◽  
Liam O'Neill
Keyword(s):  
Logistic Regression ◽  
Univariate Analysis ◽  
Survival Rates ◽  
Nursing Home Residents ◽  
Binary Logistic Regression ◽  
Hospitalized Patients ◽  
Skilled Nursing Facilities ◽  
Nursing Facilities ◽  
Skilled Nursing ◽  
Factors Associated

Abstract Background Nursing home residents were impacted disproportionately by the coronavirus because of their vulnerabilities. Although many studies concentrated on risk factors associated with mortality of hospitalized patients, there were limited studies epitomizing them from skilled nursing facilities to hospitals. The study aims to identify inpatients’ characteristics on demographics, hospital admission types, insurance types, and chronic diseases associated with mortality among our cohort patients in Texas. Methods Individuals above 50 years, diagnosed with Covid-19, and admitted from skilled nursing facilities were included in the retrospective cohort study. Pearson’s Chi-Square and Mann-Whitney tests were applied to measure four major perspectives between survivors and non-survivors. Then, a binary logistic regression was employed to determine the association between independent variables and mortality. Results A total of 218 patients were included in the study, of which 54 (24.8%) died during hospitalization. According to the univariate analysis, expired patients were more likely to be emergency admission (p = 0.001), elective admission (p = 0.02), Medicaid as primary payment (p = 0.034), heart disease (p = 0.027), CKD (p = 0.03), and hypertension (p = 0.002). The binary logistic regression revealed that hypertension (OR = 3.176, 95% CI: 1.200-8.409, p = 0.02) and Medicaid (OR = 2.637, 95% CI: 1.287-5.405, p = 0.008) as primary payment had significantly high odds of mortality. Conclusion Hypertension and Medicaid as primary payment are the strongest predictive factors associated with mortality and suggest that hospitals in Texas distribute critical care and resources while prevent and treat them to increase survival rates.

scholarly journals Value of laboratory tests in COVID-19 hospitalized patients for clinical decision-makers: a predictive model, using data mining approach

2020 ◽  
Author(s):  
Atefeh Mousavi ◽  
Soheyla Rezaei ◽  
Jamshid Salamzadeh ◽  
Ali Mirzazadeh ◽  
Farzad Peiravian ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Service Providers ◽  
Laboratory Data ◽  
Clinical Decision ◽  
Hospitalized Patients ◽  
Decision Makers ◽  
Adult Patients ◽  
Data Mining Approach ◽  
Logistic Regression Method ◽  
Using Data

Abstract Purpose: Because of the rapid increase in confirmed cases of COVID-19, in particular those with severe or critical status, overwhelming of health systems is a worldwide concern. Therefore, identifying high-risk COVID-19 patients, can help service providers for priority setting and hospital resource allocation. Methods: 4542 adult patients with confirmed COVID-19 admitted in 15 hospitals in Tehran, Iran, from Feb 20 to April 18, 2020 were included in this retrospective cohort study with final outcomes of survived and died patients. Demographic features including age and sex, and laboratory data measured at admission were extracted and compared between recovered and died patients. Data analysis was performed applying SPSS modeler software using a logistic regression method.Results: Of 4542 hospitalized adult patients, 822 patients (18.09%) died during hospitalization, and 3720 (81.90%) recovered and discharged. Based on logistic regression model, older age, 40-49 (RR= 1.80, CI: 1.13-2.87), 50-59 (RR=2.63, CI: 1.71-4.02), 60-69 (RR= 4.40, CI: 2.92-6.63), 70-79 (RR=7.49, CI: 5.01-11.19), Above 80 (RR=13.85, CI: 9.23-2.77), ALT ≥ 55 IU/ (RR=2.20, CI: 1.69-2.86), AST ≥ 100 IU/L (RR=5.93, CI: 4.75-7.39), ALP ≥ 200 IU/L (RR=2.46, CI: 1.80-3.37), sodium < 135 mEq/l (RR=1.69, CI: 1.35-2.11) or more than 145 mEq/l (RR=7.24, CI: 5.07-10.33), potassium > 5.50 mEq/l (RR=7.53, CI: 4.15-13.64), and calcium < 8.50 mEq/l (RR=3.39, CI: 2.81-4.09), CPK between 307-600 IU/L (RR=2.73, CI: 2.12-3.53) and above 600 IU/L (RR=4.41, CI: 3.40-5.71) in men, and 192-400 IU/L (RR=2.73, CI: 2.12-3.53), and above 400 (RR=4.41, CI: 3.40-5.71) in women, CRP > 3 mg/l (RR=3.22, CI: 1.99-5.20), and creatinine > 1.5 mg/l (RR=6.37, CI: 5.30-7.66) were significantly associated with COVID-19 mortality. Conclusion: Our findings suggested less than one in five hospitalized patients with COVID-19 die mostly due to electrolyte disbalance, liver, and renal dysfunctions. Better supportive care is needed to improve outcomes for patients with COVID-19.

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